AI Infrastructure Engineer

Job Description

We are seeking an AI Infrastructure Engineer to build, operate, and continuously enhance the Linux and GPU-based infrastructure that powers our AI platforms and performance testing environments. This is a highly hands-on infrastructure, automation, and performance engineering role. You will design and maintain benchmarking frameworks, ensure the reliability and security of lab and compute environments, and develop internal AI platform services that support customer demonstrations, proof-of-concepts, competitive evaluations, and technical sales efforts.

Your work will play a key role in helping secure new customer opportunities by enabling rapid validation of customer requirements and showcasing the performance and capabilities of our AI solutions.

• Operate, maintain, and enhance automated performance testing services that benchmark throughput, latency, scalability, and resource utilization.
• Develop new testing frameworks, automation, and validation methodologies as requirements evolve.
• Analyze performance data and recommend improvements to reliability, scalability, and operational efficiency.

• Deploy, monitor, and optimize Linux servers, GPU clusters, virtualization platforms, and lab hardware.
• Support availability and utilization of compute resources for engineering, testing, and AI workloads.
• Evaluate and integrate new hardware technologies to improve performance and efficiency.

• Implement monitoring, logging, alerting, failover, and incident response for critical infrastructure.
• Develop, deploy, and maintain internal AI server applications and shared compute platforms.
• Improve operational efficiency through automation and proactive issue identification; troubleshoot complex system/network/application issues.

• Support day-to-day lab operations: access control, network administration, resource allocation, and capacity planning.
• Contribute to operational standards and best practices for lab governance.

• Create and maintain technical documentation: benchmarking reports, design notes, and internal runbooks.
• Share technical insights and best practices with the broader engineering organization.

• Hands-on Linux systems administration and infrastructure experience (servers, networking fundamentals, virtualization).
• Experience with KVM or containerization (Docker/Kubernetes).
• Familiarity with Dev Ops tool chains (CI/CD, IaC, monitoring/observability stacks).
• Strong scripting/automation ability in Python and/or Bash, applied to infrastructure or testing workflows.
• Practical experience with GPU-based compute environments or AI/ML infrastructure.

• Bachelor's degree in Computer Science, Computer Engineering, or a related field (equivalent experience welcome).
• Experience with performance testing, benchmarking, or traffic-generation methodologies.
• Exposure to network security concepts and enterprise security technologies.
• Experience with Fortinet products (Forti Gate, Forti Manager, Forti Analyzer) or similar enterprise security/networking solutions — a plus, not required.
• Experience in customer-facing technical work: proof-of-concept support, demos, or technical presentations.
• Experience creating technical documentation, white papers, or delivering internal training.

• Infrastructure Engineering
• AI Platform Development
• Dev Ops & Automation
• Performance Testing & Benchmarking
• Technical Documentation

Fortinet offers employees a variety of benefits, including medical, dental, vision, life and disability insurance, 401(k), 11 paid holidays, vacation time, and sick time as well as a comprehensive leave program.

Wage ranges are based on various factors including the labor market, job type, and job level. On target earnings for this position is expected to be $215,000 - $350,000 per year. Exact salary offers will be determined by factors such as the candidate's subject knowledge, skill level, qualifications, experience, and geographic location.

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